還記得那隻將圍棋界攪得天翻地覆的“阿法狗”嗎？在隱匿一段時日後，“阿爾法圍棋”（AlphaGo）重出江湖，並且變得更加強大。這可不是一般的電腦軟件升級，而是一次人工智能的突破。
開發出“阿爾法圍棋”的英國“深度思維”公司，推出了最新版的“阿爾法圍棋—零”。
DeepMind, the London-based artificial intelligence (AI) lab announced last Wednesday that it has significantly improved its most famous AI agent: AlphaGo.
“深度思維”公司將“阿爾法圍棋”的發展分為四個階段：
第一個版本是“阿爾法圍棋－樊”，它在2015年戰勝歐洲圍棋冠軍樊麾，標誌著人工智能首次戰勝人類職業棋手；
第二個版本是“阿爾法圍棋－李”，它在2016年戰勝曾多次奪得世界冠軍的韓國棋手李世石，標誌著人工智能戰勝人類頂級棋手；
第三個版本是“阿爾法圍棋－大師”，在今年戰勝現在世界排名第一的柯潔，並在與多位有世界冠軍頭銜的人類棋手“群戰”中完勝。
那麼最新版本的“阿爾法圍棋－零”有多厲害？在開始學習圍棋3天后，“阿爾法圍棋－零”就以100比0的成績戰勝了“阿爾法圍棋－李”；21天后，它又戰勝了在所有人類高手看來已不可企及的“阿爾法圍棋－大師”。40天后，“阿爾法圍棋－零”已經擊敗了此前所有版本的“阿爾法圍棋”。
It took AlphaGo Zero just three days to beat an earlier AI program (AlphaGo Lee), which had resoundingly beaten world champion Lee Sedol in 2016. After 21 days of playing, AlphaGo Zero defeated AlphaGo Master, an intelligent program known for beating 60 top pros online and another world champion player in 2017. By day 40, AlphaGo Zero had defeated all previous AI versions of AlphaGo.
就連柯潔也感嘆，在阿爾法狗面前，“人類太多餘了”……
“阿爾法圍棋－零”團隊則在新一期英國《自然》雜誌上發表題為《在沒有人類知識條件下掌握圍棋遊戲》的論文，介紹了這一成果。
此前，“阿爾法圍棋”版本在剛開始學習圍棋時，都要依靠人類知識，即先教它們一些人類摸索出的基本下法，然後再開始自己學習。第四個版本，即最新的“阿爾法圍棋－零”擺脫了這個限制，研究人員沒有給它除棋盤和棋子之外的任何輸入，它完全是“從零開始”，自己與自己對弈，通過更為優秀的算法，取得飛速進步。
The main difference between the old AlphaGo AIs and the new one is that one learns how to play Go from human data and one doesn't. All previous versions of AlphaGo started by training on human data (amateur and professional Go matches) that was downloaded from online sites. They looked at thousands of games and were told what moves human experts would make in certain positions. But AlphaGo Zero doesn't use any human data whatsoever. Instead, AlphaGo Zero has learned how to play Go for itself, completely from self play.
DeepMind AlphaGo Zero項目領導人David Silver表示：“不使用人類的數據、特點，不做任何專業引導，我們實際上解除了人類知識的約束。它就能自己創造知識，從無到有，用自己的策略、方式去下棋。這也讓它比以往的版本更強大。”
“By not using this human data, features, or expertise in any fashion, we've actually removed the constraints of human knowledge. It's able to therefore create knowledge for itself from first principles, from a blank slate, and work out its own strategies, and its own novel ways of playing the game. This enables it to be much more powerful that previous versions." said lead AlphaGo researcher David Silver.
（綜合來源：新華網、Mashable）
